Articles | Volume 13, issue 11
Biogeosciences, 13, 3305–3317, 2016
https://doi.org/10.5194/bg-13-3305-2016
Biogeosciences, 13, 3305–3317, 2016
https://doi.org/10.5194/bg-13-3305-2016

Research article 06 Jun 2016

Research article | 06 Jun 2016

Modelling interannual variation in the spring and autumn land surface phenology of the European forest

Victor F. Rodriguez-Galiano et al.

Viewed

Total article views: 1,992 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,168 728 96 1,992 286 70 77
  • HTML: 1,168
  • PDF: 728
  • XML: 96
  • Total: 1,992
  • Supplement: 286
  • BibTeX: 70
  • EndNote: 77
Views and downloads (calculated since 30 Jul 2015)
Cumulative views and downloads (calculated since 30 Jul 2015)

Cited

Saved (preprint)

Latest update: 28 Oct 2021
Download
Short summary
This research reveals new insights into the weather drivers of land surface phenology (LSP) across the entire European forest, while at the same time it establishes a new conceptual framework for modelling LSP. Specifically, a sophisticated machine learning regression method (RF) was introduced for LSP modelling across very large areas and across multiple years simultaneously. The RF models explained 81 and 62 % of the variance in the spring and autumn LSP interannual variation.
Altmetrics
Final-revised paper
Preprint